Probabilistic Event-driven Fault Diagnosis Through Incremental Hypothesis Updating

Abstract: A probabilistic event-driven fault localization technique is presented, which uses a symptom-fault map as a fault propagation model. The technique isolates the most probable set of faults through incremental updating of the symptom explanation hypothesis. At any time, it provides a set of alternative hypotheses, each of which is a complete explanation of the set of symptoms observed thus far. The hypotheses are ranked according to a measure of their goodness. The technique allows multiple simultaneous independent faults to be identified and incorporates both negative and positive symptoms in the analysis. As shown in a simulation study, the technique is resilient both to noise in the symptom data and to the inaccuracies of the probabilistic fault propagation model. 1

• Type: Conference
• Year: 2003
• Where: IM
• Authors: Malgorzata Steinder, Adarshpal S. Sethi
• Keywords: Fault Localization Technique, Fault Propagation Model, IM 2003, IM 2007, Symptom